Day-Ahead Operational Planning for DisCos Based on Demand Response Flexibility and Volt/Var Control
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- Lu, Renzhi & Hong, Seung Ho & Zhang, Xiongfeng, 2018. "A Dynamic pricing demand response algorithm for smart grid: Reinforcement learning approach," Applied Energy, Elsevier, vol. 220(C), pages 220-230.
- Vijayan, Vineeth & Mohapatra, Abheejeet & Singh, S.N., 2021. "Demand Response with Volt/Var Optimization for unbalanced active distribution systems," Applied Energy, Elsevier, vol. 300(C).
- Anthony Igiligi & Armin Vielhauer & Mathias Ehrenwirth & Christian Hurm & Thorsten Summ & Christoph Trinkl & Daniel Navarro Gevers, 2023. "Assessment of Conservation Voltage Reduction in Distribution Networks with Voltage Regulating Distribution Transformers," Energies, MDPI, vol. 16(7), pages 1-14, March.
- Eduardo J. Salazar & Mauro Jurado & Mauricio E. Samper, 2023. "Reinforcement Learning-Based Pricing and Incentive Strategy for Demand Response in Smart Grids," Energies, MDPI, vol. 16(3), pages 1-33, February.
- Benedetto-Giuseppe Risi & Francesco Riganti-Fulginei & Antonino Laudani, 2022. "Modern Techniques for the Optimal Power Flow Problem: State of the Art," Energies, MDPI, vol. 15(17), pages 1-20, September.
- Papadimitrakis, M. & Giamarelos, N. & Stogiannos, M. & Zois, E.N. & Livanos, N.A.-I. & Alexandridis, A., 2021. "Metaheuristic search in smart grid: A review with emphasis on planning, scheduling and power flow optimization applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
- Ikeda, Shintaro & Ooka, Ryozo, 2019. "Application of differential evolution-based constrained optimization methods to district energy optimization and comparison with dynamic programming," Applied Energy, Elsevier, vol. 254(C).
- Umar Waleed & Abdul Haseeb & Muhammad Mansoor Ashraf & Faisal Siddiq & Muhammad Rafiq & Muhammad Shafique, 2022. "A Multiobjective Artificial-Hummingbird-Algorithm-Based Framework for Optimal Reactive Power Dispatch Considering Renewable Energy Sources," Energies, MDPI, vol. 15(23), pages 1-23, December.
- Jin, Ming & Feng, Wei & Marnay, Chris & Spanos, Costas, 2018. "Microgrid to enable optimal distributed energy retail and end-user demand response," Applied Energy, Elsevier, vol. 210(C), pages 1321-1335.
- Bostan, Alireza & Nazar, Mehrdad Setayesh & Shafie-khah, Miadreza & Catalão, João P.S., 2020. "Optimal scheduling of distribution systems considering multiple downward energy hubs and demand response programs," Energy, Elsevier, vol. 190(C).
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Keywords
active distribution systems; demand response; Volt/Var control; genetic algorithm; dynamic programming; forecasting; behind-the-meter; deep learning;All these keywords.
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